Research on Cognition and Inference Model of Interface Color Imagery Based on EEG Technology

Abstract

The mobile phone interface has become important access to daily information and social entertainment. And the color design of digital interfaces has a direct impact on improving the user experience. In order to explore the user's perceptual cognition of the interface color imagery, the objective relationship between EEG (Electroencephalography) signal and interface color imagery cognition is analyzed and an inference model of interface color imagery based on EEG is established. Imagery words were selected by a card sorting experiment. EEG data is generated in the users' cognition process of matching app interface color and imagery words. Experimental results show that the N400 component appears in the experiment of imagery word as the target stimulus, and the P300 component appears in the experiment of interface picture as the target stimulus. The inference model of interface color imagery is established by Extreme Learning Machine (ELM) based on the average amplitude data of N400 or P300. Results of the verification experiment indicate that the inference model can accurately predict the imagery match tendency of interface color and imagery words.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research was supported by the National Natural Science Foundation of China under Grant [62002321] and Scientific Research Foundation of Zhejiang University City College (No.X-202203).

Notes on contributors

Cheng Yang

Cheng Yang is a professor in the Industrial Design Department of Zhejiang University City College, responsible for the Digital Intelligence Design Lab. He received his PhD in Digital Media Design from Zhejiang University. His research interests include brain-computer interaction system design, intelligent design, and digital creative design.

Lei Kong

Lei Kong is a master student in Industrial Design Engineering from the School of Computer Science and Technology, Zhejiang University. Her research interest is system design for brain-computer interaction.

Zhichao Zhang

Zhichao Zhang is a master student in Industrial Design Engineering from the School of Computer Science and Technology, Zhejiang University. His research interest is system design for brain-computer interaction.

Yiteng Peng

Yiteng Peng is a master student in Industrial Design Engineering from the School of Computer Science and Technology, Zhejiang University. Her research interest is system design for brain-computer interaction.

Qian Wang

Qian Wang is a master student in Industrial Design Engineering from the School of Computer Science and Technology, Zhejiang University. Her research interest is neural design.

Ye Tao

Ye Tao is an associate professor of the Industrial Design Department of Zhejiang University City College, a visiting scholar of the Human-Computer Interaction Department of Carnegie Mellon University, and a postdoctoral fellow of the Industrial Design Department of Zhejiang University. Her research interests include digital design, digital manufacturing, and humanistic handicrafts.

Yu Song

Yu Song is an associate professor in the Visual Communication Design Department of Zhejiang University City College. Her research interest is digital media design.